Product Requirement Ambiguity Detection
Given a product requirement, identify undefined actors, missing states, conflicting constraints, untestable language, and unanswered acceptance questions.
Compare 2 router rates · observed 9/4/2026
Compare 2 router rates · observed 9/11/2026
Compare 2 router rates · observed 9/11/2026
All 12 model results and methodology
Generated 97/100 examples — partial set accepted at the success threshold
| Model | Tier | Quality | Judged | Scenario cost |
|---|---|---|---|---|
| Nemotron Nano 9B v2 | small | 82% | 97/97 | $40.26 |
| Qwen3 235B A22B | mid | 92% | 97/97 | $257 |
| DeepSeek V3 | mid | 99% | 97/97 | $110 |
| Mistral Large 2407 | mid | 94% | 97/97 | $130 |
| Arcee Trinity Large Thinking | mid | 98% | 97/97 | $130 |
| GPT-5.4 | frontier | 25% | 97/97 | $3057 |
| Claude Opus 4.7 | frontier | 18% | 97/97 | $5191 |
| Gemini 3.1 Pro Preview | frontier | 18% | 97/97 | $2423 |
| Gemma 4 E4B IT | small | 89% | 97/97 | $12.17 |
| Granite 4.1 8B | small | 92% | 97/97 | $10.89 |
| Ministral 8B Instruct 2410 | small | 63% | 97/97 | $15.21 |
| Qwen3 4B Instruct 2507 | small | 71% | 97/97 | $120 |
LLM-judge pass rate on 97 synthetic examples. Generator: gpt-5.2. Judge: gpt-5.2. Evaluated 2026-09-10T08:54:53.273Z.
Directional: measured on a synthetic eval set generated by drydock. Cost/latency are not yet captured for taskrouter-run benchmarks.
drydock